Prevalence of anemia among under-5 children in the Ghanaian population: estimates from the Ghana demographic and health survey
Bibliographic record
Abstract
BACKGROUND: Anemia in children continues to be a major public health challenge in most developing countries, particularly in Africa. Anemia in the early stages of life leads to severe negative consequences on the cognitive as well as the growth and development of children, which may persist even after treatment. We examine the prevalence of anemia in under-five children in the Ghanaian population to help inform and serve as a guide to health policies and possible interventions. METHODS: Data from the 2008 Ghana Demographic and Health Survey (GDHS) was used. Data consists of health, demographic and socio-economic factors. Anemia status was determined using hemoglobin level, and prevalence of childhood anemia along with 95% confidence intervals was provided. We also examined the distribution of prevalence across different age and socio-demographic groups as well as the different regions and sub-regions in Ghana. RESULTS: The overall prevalence of anemia in under-five children in Ghana was 78.4% (N = 2168, 95% CI: 76.7-80.2), where 7.8% (N = 2168, 95% CI: 6.6-8.9) of the children had severe anemia, 48.0% (N = 2168, 95% CI: 45.9-50.2) moderate anemia and 22.6% (N = 2168, 95% CI: 20.8-24.4) had mild anemia. The highest prevalence regions were the Upper East, 88.9% (N = 158, 95% CI: 80.9-94.0), and Upper West 88.1% (N = 220, 95% CI: 76.4-94.6). The prevalence was also higher among children under 2 years of age, 85.1% (N = 781, 95% CI: 82.6-87.7) than children 2-5 years of age, 74.8% (N = 1387, 95% CI: 72.5-77.1). No significant difference in prevalence between boys and girls was observed. CONCLUSIONS: Given the high prevalence of childhood anemia observed in Ghana, particularly among those less than 2 years old, and given the negative consequences on their cognitive and behavioral development even in later years, there is an urgent need for effective and efficient public health interventions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".